Toward Fault-Tolerant Vehicle Motion Control for Over-Actuated Automated Vehicles: A Non-Linear Model Predictive Approach

Abstract

Automated driving systems operated at SAE levels 4 and 5 require a far-reaching fault-tolerant design. To meet this need at the actuator level, we present an integrated vehicle motion control approach that is able to tolerate a wide range of different actuator degradations and failures as well as tire blowouts in vehicles featuring four wheel-individual steering, drive, and brake actuators. The approach, which is based on non-linear model predictive control (MPC), tracks a temporal sequence of reference poses. Fault tolerance is achieved by reconfiguration of the MPC's constraints, weights, and prediction model, which consists of a double-track vehicle and a brush tire model. The evaluation of the approach is based on two reference trajectories. The example of a simple single lane change trajectory in IPG CarMaker demonstrates the basic functionality of the approach. The example of a demanding decelerated single lane change trajectory shows that the approach is subject to limitations when tolerating different degradations and failures. Still, the observed limitations can be explained by the interplay of the specific degradation or failure and the demanding nature of the trajectory. Therefore, the results indicate that the suitability of fault-tolerant vehicle motion control as part of a system-wide safety concept is strongly connected to the range of possible driving scenarios that an automated driving system can encounter.

ODD-Centric Contextual Sensitivity Analysis Applied To A Non-Linear Vehicle Dynamics Model

“…Second, the reference trajectory is applied to the model-predictive trajectory controller which generates the required control signals. The applied MPC algorithm is described by Stolte et al [8] and utilizes a complex nonlinear double-track vehicle dynamics model. To determine the sensitivity of the vehicle dynamics model integrated in the MPC algorithm along the reference trajectory, the trajectory controller is connected to an identical vehicle dynamics model in a closed loop which mirrors the model integrated in the controller and provides the required feedback.…”

“…In a MATLAB/SIMULINK simulation environment, we apply the generated reference trajectory to the model-based trajectory controller by [8] in a closed loop with the nonlinear doubletrack vehicle dynamics model. A Magic Formula Tire Model [30] is integrated in the state-space representation of the vehicle dynamics model in our implementation.…”

“…Optimal trajectories with respect to vehicle dynamics can be planned and controlled using the model knowledge (e.g. [6][7][8]). The quality of such approaches directly depends on the quality of the underlying vehicle models.…”

Crash-Prone Fault Combination Identification for Over-Actuated Vehicles During Evasive Maneuvers

“…FTC for steering failure and faults have been proposed in [15]- [17]. The authors in [15] presented an FTC to handle one steering failure at a time.…”

“…At a double lane change in a non-evasive situation, the controller handled the maneuver up to 60 km/h on a dry surface. The approch in [17] presented an active MPC-FTC, with controller parameter reconfiguration in case of single actuator failure or fault. The test scenarios consisted of, firstly, a vehicle at 50 km/h performing a single lane change of 60 meters and, secondly, driving up to 80 km/h in a single lane change of 60 meters followed by deceleration.…”